[Numpy-discussion] Rationale for returning type-wrapped min() / max() scalars? (was: Problem with ufunc of a numpy.ndarray derived class)

[Hans Meine]

Am Freitag, 29. Juli 2011, 11:31:24 schrieb Hans Meine:
> Am Donnerstag, 28. Juli 2011, 17:42:38 schrieb Matthew Brett:
> > Was there a particular case you ran into where this was a problem?
> [...]
> Basically, the problem arose because our ndarray subclass does not support
> zero-rank-instances fully.  (And previously, there was no need for that.)

I just reproduced the problem, it was this exception:

/home/hmeine/new_numpy/lib64/python2.6/site-packages/vigra/arraytypes.pyc in 
reshape(self, shape, order)
    587 
    588     def reshape(self, shape, order='C'):
--> 589         res = numpy.ndarray.reshape(self, shape, order)
    590         res.axistags = AxisTags(res.ndim)
    591         return res

TypeError: an integer is required

The problem is that 'self' has become a zero-rank array, and those cannot be 
reshaped in order to add singleton dimensions anymore.  IOW, if you implement 
sth. like broadcasting, this is made much harder.

Best,
  Hans